1. Field of the Invention
This invention relates to an image processing method and apparatus for carrying out a predetermined filtering process on an original image signal, thereby forming an unsharp mask image signal, and carrying out nonlinear processing, such as frequency emphasis processing, by using the unsharp mask image signal. This invention particularly relates to characteristics of a filter utilized for forming the unsharp mask image signal.
2. Description of the Prior Art
The applicant has proposed various image processing methods and apparatuses, wherein frequency emphasis processing or dynamic range compression processing is carried out by using an unsharp mask image signal, and a radiation image, which has good image quality and can serve as an effective tool in, particularly, the efficient and accurate diagnosis of an illness, is thereby obtained. (Such techniques are described in, for example, U.S. Pat. Nos. 4,315,318; 4,317,179; 5,454,044 and U.S. Ser. No. 08/723,313.)
The unsharp mask image signal represents an image, which is constituted of the same number of picture elements as that of the picture elements of the original image, which is represented by an original image signal, and has sharpness lower than the sharpness of the original image. The unsharp mask image signal is formed by carrying out a predetermined filtering process with respect to each of picture elements of the original image represented by the original image signal, which are selected at predetermined intervals, thereby thinning out the picture elements, and thereafter interpolating the picture elements, which were removed by the filtering process, in accordance with a predetermined interpolating operation.
As the predetermined filtering process, a process for removing high frequency components of the original image signal by using a low pass filter is employed. Specifically, a process for calculating the mean value or the weighted mean value of the values of the picture elements located within a filter is employed. In an example of the filtering process, after the filtering process has been carried out on the original image signal and a signal representing an image constituted of a smaller number of picture elements than that of the picture elements of the original image has been obtained, the filtering process is repeated on the thus obtained signal. In this manner, a plurality of image signals representing the images constituted of a small number of picture elements are obtained in the respective stages of the filtering. An interpolating operation is then carried out on each of the thus obtained image signals, and signals representing images constituted of the same number of picture elements as that of the picture elements of the original image are thereby obtained. In this manner, a plurality of different unsharp mask image signals are formed.
Each of the thus formed unsharp mask image signals represents the components of the original image signal, which fall within a predetermined frequency band. Also, a signal representing the frequency components of a further limited frequency band can be obtained by calculating the difference between different unsharp mask image signals. Such a technique is employed when the components of the original image signal, which fall within a specific frequency band, are to be processed in frequency emphasis processing, dynamic range compression processing, or the like. For example, nonlinear processing is carried out, wherein frequency emphasis is conducted by restricting the signal of a specific frequency band and adding the resulting signal to the original image signal.
As described above, the unsharp mask image signal is formed from the original image signal. The original image signal is obtained by reading out the original image with a predetermined read-out density by use of a read-out apparatus and thereby obtaining a digital signal. It has been known that, when a visible image is reproduced as a print, or the like, from the digitized image signal, the frequency components not higher than a certain frequency (Nyquist frequency), which is determined by the read-out density, are reproduced accurately. Specifically, the read-out density is determined by considering the image quality level required for the reproduced image, and therefore is not necessarily set to be a fixed value.
For example, in radiation image read-out and reproducing systems described in the references cited above, a stimulable phosphor sheet, on which a radiation image of an object, such as a human body, has been recorded, is scanned with a laser beam, and the radiation image is thereby read out as a digital image signal. The read-out density is set to be one of different values in accordance with the size of the stimulable phosphor sheet.
In cases where filtering processes with the same low pass filter and interpolating processes with the same interpolating operation are carried out on image signals, which have been obtained with different read-out densities, i.e. the image signals having different Nyquist frequencies, the frequency characteristics of the obtained unsharp mask image signals vary for different read-out densities. Therefore, the problems occur in that, for example, in cases where a single original image is read out with two kinds of read-out densities and two kinds of original image signals representing the original image are thereby obtained, even if the frequency emphasis processing or the dynamic range compression processing is carried out by using the same unsharp mask image signal, the frequency band, which is emphasized, or the frequency band, which is compressed, will vary for the two kinds of the original image signals.